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Application of computing and communications intelligence effectively improves the quality of monitoring and control of smart grids. However, the dependence on information technology also increases vulnerability to malicious attacks. False data injection (FDI), that attack on the integrity of data, is emerging as a severe threat to the supervisory control and data acquisition system. In this paper,...
In this paper, we propose a privacy-preserving middleware mechanism for managing the massive data flows in smart grids and securing the communications. In our proposed middleware mechanism, we exploit the deep learning techniques and develop a privacy-preserving deep convolutional neural network (DCNN)-based method that leverages the public network infrastructure for intrusion detection. The simulation...
In recent years, the increasing penetration of Distributed Energy Resources (DERs) has made an impact on the operation of the electric power systems. In the grid integration of DERs, data acquisition systems and communications infrastructure are crucial technologies to maintain system economic efficiency and reliability. Since most of these generators are relatively small, dedicated communications...
In this paper, we propose a game theoretic modelling paradigm for the energy trading market of a Microgrid Social Network (MGSN) architecture in which the networked Microgrids (MGs) are connected by a common physical bus and social networks. In the considered MGSN, individual MGs involved in energy trading, called market participants, make decision on energy trading based on the state estimation of...
In recent years, Microgrids (MGs), a widely acceptable smaller-scale energy infrastructure, are proved to be valuable in their resilience and reliability specially during extreme disasters that cause blackouts and major grid instabilities and being positioned to represent modulator building blocks for critical energy infrastructure in future sustainable smarter cities. In this paper, we propose a...
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